Accuracy of Xpert MTB/RIF assay for the diagnosis of tuberculous pleural effusion

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Abstract

Background: Tuberculosis poses a severe threat to human health. At present, compared with the traditional diagnostic methods for tuberculosis pleural effusion, such as Löwenstein–Jensen culture, pleural biopsy, and Ziehl–Neelsen smear microscopy, Xpert MTB/RIF was regarded as an emerging technology for its efficiency. The Xpert MTB/RIF accuracy for tuberculous pleural effusion diagnosis was evaluated in this systematic study. Materials and methods: We searched the relevant literature published before January 2021 in PubMed, Cochrane, EMBASE, and Web of Science databases. Utilizing Review Manager 5.3 software, the quality of the included literature was evaluated based on the Quality Assessment of Diagnostic Accuracy Studies criteria. Sensitivity, specificity, and the summary receiver operating characteristic curves were plotted and analyzed with Metadisc 1.40 software. We used Stata 12.0 software to evaluate the publication bias of this study. Results: Eighteen articles were identified in total. The sensitivity of Xpert MTB/RIF in the pleural effusion was 0.24, and specificity was 1.00, respectively. The area under the summary receiver operating characteristic curve was 0.9737, which indicated that the overall accuracy of the Xpert MTB/RIF was high. In addition, based on the Deeks funnel plot, no publication bias of the study was found. Conclusion: Xpert MTB/RIF is a rapid method with high specificity but relatively low sensitivity for detecting Mycobacterium tuberculosis in pleural effusion. Its less sensitivity made it difficult to be used clinically, but the high specificity suggests that it can be used as a specific diagnostic method for tuberculous pleural effusion.

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Qiu, Y. R., Chen, Y. Y., Wu, X. R., Li, Y. P., Cao, X. J., Yu, Z. Y., … Guo, X. G. (2022). Accuracy of Xpert MTB/RIF assay for the diagnosis of tuberculous pleural effusion. Journal of Clinical Laboratory Analysis, 36(1). https://doi.org/10.1002/jcla.24185

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